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Hindawi Publishing Corporation Journal of Climatology Volume 2013, Article ID 928501, 8 pages http://dx.doi.org/10.1155/2013/928501

Research Article Recent Extreme Precipitation and Changes in City (1966–2011)

Pierre Ozer1 and Ayan Mahamoud2

1 Department of Environmental Sciences and Management, University of Liege,` Avenue de Longwy 185, 6700 Arlon, Belgium 2 Research Center, Department of Geomatics and Environmental Sciences, University of Djibouti, Avenue Georges Clemenceau, BP 1904, Djibouti

Correspondence should be addressed to Pierre Ozer; [email protected]

Received 21 March 2013; Accepted 3 October 2013

Academic Editors: A. V. Eliseev, S. Feng, P. Gober, and S. Gualdi

Copyright © 2013 P. Ozer and A. Mahamoud. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

A dataset of 23 derived indicators has been compiled to clarify whether the frequency of rainfall and temperature extremes has changed over the last decades in Djibouti City, eastern . Results show that all precipitation indices have declined over the last decades, although only the very wet day frequency and the very wet day proportion present a significant decline. Annual total precipitation has decreased by 17.4% per decade from 1980 to 2011 and recent mean yearly rainfall (44 mm on average from 2007 to 2011) meets a 73% deficit compared to the 30-year (1981–2010) average (164 mm). The average temperature increase is ∘ ∘ +0.28 C per decade.Extremely warm days (maximum temperature ≥45.0 C) have become 15 times more frequent than in the past ∘ while extremely cool nights (minimum temperature ≤8.6 C) have almost disappeared. Current rainfall shortages and increasing temperature extremes are impacting local people who urgently need adaptation strategies.

1. Introduction cold days, cold nights, and frost have become less frequent over most land areas, while hot days and hot nights have Warming of the system is unequivocal, as is now become more frequent. It is also likely that heatwaves have evident from observations of increases in global average air become more frequent and that the frequency of heavy and ocean , widespread melting of snow and ice precipitation events (or proportion of total rainfall from and rising global average sea level [1]. heavy falls) has increased over most areas [1]. According to the Climate Research Unit of the Univer- In addition to the climate change impacts, population sity of East Anglia [2], global air temperature during the andinfrastructurecontinuetodevelopinareasthatare ∘ ∘ period 2001–2010 (0.48 C above 1961–1990 mean) was 0.22 C vulnerable to extremes such as flooding, storm damage, ∘ warmer than that in the 1991–2000 decade (0.27 Cabove and extreme temperatures. Furthermore, land use change 1961–1990 mean). The warmest year of the entire series (1850– can often further increase vulnerability by creating more ∘ 2012) was 2010, with a temperature of 0.54 Cabovethe1961– potential for catastrophic impacts from climate extremes, 1990 mean. After 2010, the next ten warmest years in the series such as flooding due to extreme precipitation events. are all in the period 1998–2012. Most of the observed increase Although the frequency, the intensity, and the impacts of in global average temperatures since the mid- extreme weather events are well documented in most parts of isverylikelyduetotheobservedincreaseinanthropogenic theworld,therehasbeenpaucityofinformationontrendsin greenhouse gases (GHGs) concentrations [1]. daily extreme rainfall events in Africa [3]. The lack of long- Some extreme weather events have received increased term daily climate data suitable for analysis of extremes is the attention in the last few years within the perspective of climate biggest obstacle to quantifying whether extreme events have change. Studies show that they have changed in frequency changed over the last decades, either continental or on a more and/or intensity over the last 50 years. Yet, it is very likely that regional basis [4]. 2 Journal of Climatology

Main railway Main International boundary District boundary Main airport Capital Major town Other town August 2006

(km) 0 10 20 30 40

0 10 20 (mi)

Figure 1: Location of the Republic of Djibouti and Djibouti City.

In this paper, evidence for changes in the intensity of 100 50 extreme daily rainfall and temperature events during the last decades is assessed in the Republic of Djibouti, the 80 40 C)

smallest in the bordered by ∘ in the north, in the west and south, in the 60 30 southeast, and facing the and the Gulf of at the 2 east. The country occupies a total area of about 23,200 km 40 20 Rainfall (mm)

(Figure 1). ( Temperature According to the Koppen-Geiger¨ world climate classifi- 20 10 cation, the climate of the Republic of Djibouti is defined as a hot (BWh) [5]. Hot conditions prevail year-round 0 0 ∘ J FMAASOND MJJ with monthly average temperatures ranging from 25.4 Cin ∘ January to 36.8 C in July, while rainfall are very scarce all T Rainfall max T T year-long with monthly total precipitation below 10 mm from min moy May to August and between 10 and 28 mm the rest of the year (Figure 2). As in many arid , annual rainfall is Figure 2: Monthly distribution of rainfall and temperature in significantly irregular and extreme rainfall can be observed in Djibouti City (average 1981–2010). anumberofyears[6]. We use here meteorological data from the unique synoptic station of the country, Djibouti airport, ∘ located south of the of Djibouti City (Figure 1). the synoptic station of Djibouti City (Lat: 11.55 N; Long: ∘ 43.15 E; altitude: 13 m asl, WMO station code: 63125) located 2. Data and Methods near the International Airport of Djibouti from the “Agence Nationale de la Met´ eorologie´ (ANM) de Djibouti.” The 2.1. Database. For the analysis of recent trends of extreme airport is located outside and south of the capital city. The precipitation and temperatures, data were made available for database includes daily precipitation data from January 1980 Journal of Climatology 3

Table 1: Rainfall and temperature indices with their definitions and units.

ID Indicator name Definition Unit PTOT Precipitation total Annual total precipitation mm Rd Rainfall days Annual total of wet days (rainfall ≥1 mm) days SDII Simple day intensity index Average rainfall from wet days mm/day Rx1d Maximum 1-day rainfall Annual maximum 1-day rainfall mm R10 mm Number of heavy precipitation days Annual count of days when rainfall ≥10 mm days R20 mm Number of very heavy precipitation days Annual count of days when rainfall ≥20 mm days ≥ R95p Very wet day frequency Annual count of days when rainfall 95th percentile of days 1981–2010 ≥ R99p Extreme rainfall frequency Annual count of days when rainfall 99th percentile of days 1981–2010 ≥ R95pSUM Very wet day intensity Annual precipitation from days when rainfall 95th mm percentile of 1981–2010 ≥ R99pSUM Extreme rainfall intensity Annual precipitation from days when rainfall 99th mm percentile of 1981–2010 R95pTOT Very wet day proportion Percentage of annual precipitation from days when % rainfall ≥95th percentile of 1981–2010 R99pTOT Extreme rainfall proportion Percentage of annual precipitation from days when % rainfall ≥99th percentile of 1981–2010 ∘ ATN Average annual 𝑇min Annual average value of daily minimum temperature C ∘ ATX Average annual 𝑇max Annual average value of daily maximum temperature C 𝑇 ∘ ATM Average annual mean Annual average value of daily mean temperature C Annual count of days when 𝑇min ≤1th percentile of TN1p Extreme cool night ∘ days 1971–2000 (18.6 C)

Annual count of days when 𝑇min ≤5th percentile of TN5p Cool night ∘ days 1971–2000 (20.2 C)

Annual count of days when 𝑇min ≥95th percentile of TN95p Warm night ∘ days 1971–2000 (32.2 C)

Annual count of days when 𝑇min ≥99th percentile of TN99p Extreme warm night ∘ days 1971–2000 (33.6 C)

Annual count of days when 𝑇max ≤1th percentile of TX1p Extreme cool day ∘ days 1971–2000 (27.5 C)

Annual count of days when 𝑇max ≤5th percentile of TX5p Cool day ∘ days 1971–2000 (28.5 C)

Annual count of days when 𝑇max ≥95th percentile of TX95p Warm day ∘ days 1971–2000 (43.9 C)

Annual count of days when 𝑇max ≥99th percentile of TX99p Extreme warm day ∘ days 1971–2000 (45.0 C) to December 2011 and maximum, minimum, and mean daily percentiles which define a very wet day and an extreme temperatures from January 1966 to December 2011. There rainfall event, respectively [7–13]. These percentile values were no missing data, so the database can be used for trend were calculated from daily rainfall data over the 1981–2010 analysis [7]. period. For the station of Djibouti City, the thresholds cal- culated from percentiles are 46.9 mm and 108.1 mm to define a very wet day and an extreme rainfall event, respectively. 2.2. Extreme Rainfall Indices. In this study, 12 rainfall indices Based on these percentiles, two extreme precipitation indices were calculated over the January to December period and were chosen. Very wet day and extreme rainfall frequency arelistedinTable 1.Thesearetheannualtotalprecipitation are based on the annual count of days when rainfall ≥95th (PTOT), the annual total of wet days (with daily rainfall and 99th percentiles of 1981–2010 (R95p and R99p). Very ≥1 mm, Rd), the simple day intensity index (SDII) that was wet day and extreme rainfall intensity correspond to the calculated as the average rainfall from wet days, the annual annual total precipitation recorded from days when rainfall maximum rainfall recorded during 1 day (Rx1d), and the ≥95th and 99th percentiles of 1981–2010 (R95pSUM and number of heavy precipitation (rainfall ≥10 mm, R10 mm) R99pSUM) and give an indication on the rain received from and very heavy precipitation (rainfall ≥20 mm, R20 mm) very wet or extreme rainfall. Very wet day and extreme days. Other six indices are based on the 95th and 99th rainfall proportion are the percentage of the annual total 4 Journal of Climatology

PTOT Rd 500 35 y = −3.8x + 218 30 y = −0.23x + 17.3 400 R2 = 0.08 R2 = 0.10 P = 0.10 25 P = 0.07 300 20

200 15 Rainfall (mm)

Rainfall days 10 100 5

0 0 1980 1985 1990 1995 2000 2005 2010 1980 1985 1990 1995 2000 2005 2010 Year Year (a) (b)

Rx1d R95p 200 4 y = −1.6x + 79.8 y = −0.04x + 1.31 160 R2 = 0.09 R2 = 0.16 P = 0.09 3 P = 0.03 120 2 80 Very wet days wet Very 1 40 Max daily rainfall (mm) rainfall daily Max

0 0 1980 1985 1990 1995 2000 2005 2010 1980 1985 1990 1995 2000 2005 2010 Year Year (c) (d)

Figure 3: Evolution and trends of PTOT, Rd, Rx1d, and R95p in Djibouti City (1980–2011). precipitation recorded from days when rainfall ≥95th and during 1980–2011 period for precipitation and 1966–2011 99th percentiles of 1981–2010 (R95pTOT and R99pTOT) and period for temperatures. This method is now extensively used measure how much total rain comes from very wet or extreme worldwide [7–13]. Each slope (positive or negative) was cat- events. egorized in six classes indicating very significant, significant, or nonsignificant trends. The regression procedure supplies a 2.3. Extreme Temperature Indices. The analysis of minimum, Student 𝑡-test and its resulting significance 𝑃 level to analyse maximum, and mean temperatures is based on 11 indices the hypothesis that the slope is equal to 0. This 𝑃-level was calculated over the January to December period (Table 1). used as a criterion to define the class boundaries. The trends, Three of them are based on the annual average value of daily for each index, were labelled as “very significant” if the 𝑃- minimum, maximum, and mean temperatures (ATN, ATX, level exceeded 0.01 for the one-tailed 𝑡-test, “significant” if and ATM) in order to analyse the global trends in tempera- the 𝑃-level ranged between 0.01 and 0.05, and otherwise tures. All other indices are based on the 1st, 5th, 95th, and 99th “nonsignificant” if the 𝑃-level is up to 0.05. percentiles which define “extremely cool,” “cool,” “warm,” and “extremely warm” nights (using 𝑇min)anddays(using 𝑇max), respectively, (adapted from [10–13]). These percentile 3. Results values were calculated from daily rainfall data over the 1971– 2000 period. Threshold temperature values calculated from 3.1. Precipitation. Time series of several precipitation indices percentiles are presented in Table 1. In Djibouti, an extremely canbeseeninFigure 3.Allindicesshowdecreasing ∘ cool night is characterized by minimum temperatures ≤8.6 C trends although most of them are statistically nonsignificant while an extremely warm day is defined when maximum (Table 2). Yet, the annual total precipitation (PTOT), the ∘ temperatures are ≥45.0 C. rainfall days (Rd), the annual maximum rainfall recorded during 1 day (Rx1d), and the very wet day rainfall intensity 2.4. Trend Analysis. In the analysis, trend coefficients are (R95pSUM) decrease in a moderate way. Only the very determined using linear regression modelling, which rep- wet day frequency (R95p) and the very wet day proportion resent the increasing or decreasing rate of the given index (R95pTOT) present a significant decline. It is likely that Journal of Climatology 5

Table 2: Rainfall trends analysis from 1980 to 2011.

ID Unit Average Trend Significance Trend 1981–2010 units/decade (P level) %/decade PTOT mm 164 −38.0 0.10 −17.4 Rd days 14.1 −2.3 0.07 −13.5 SDII mm/day 11.1 −0.5 0.70 −4.2 Rx1d mm 56.4 −15.6 0.09 −19.5 R10 mm days 3.9 −0.5 0.38 −10.7 R20 mm days 2.1 −0.5 0.27 −16.7 R95p days 0.70 −0.39 0.03 −30.2 R99p days 0.13 −0.07 0.26 −29.7 R95pSUM mm 59.7 −31.4 0.07 −29.1 R99pSUM mm 21.3 −11.5 0.28 −29.5 R95pTOT % 23.4 −14.2 <0.01 −31.3 R99pTOT % 5.8 −3.7 0.20 −32.1 the extreme rainfall events (R99p) decline may be signifi- has decreased significantly. Trends of extremes are shown in cant but it is difficult to make statistics on such a limited Figure 4. sample. The most significant rainfall shortage is found over the 4. Discussion last five years (see Figure 3).Yet,since2007,theyearly rainfall average has been 44 mm, which is an extreme rainfall Lack of long-term climate data suitable for analysis of deficit of near 75% when compared to the 1981–2010 average extremes is the biggest obstacle to quantifying whether (164 mm). During this same recent period, the synoptic extreme events have changed over the last decades in Africa. station of Djibouti City did not record any extreme rainfall This paper presents, for the first time, the analysis of extreme nor very wet day events. The maximum rainfall recorded precipitation and temperatures in Djibouti City. during 1 day was 46 mm over the last five years. Results show that all rainfall indices have declined over These data are of the highest importance in terms of the last 32 years, although only the very wet day frequency vulnerability evolution as well as future adaptation strategies (R95p) and the very wet day proportion (R95pTOT) present to natural hazard reduction, especially concerning . a significant decline. Such recent decrease in annual total This aspect will be discussed afterwards. precipitation (PTOT) is in line with recent findings in the Arab [12], over the Great Horn of Africa region [13], in the Arabian Peninsula [14], or in Ethiopia [15]andis 3.2. Temperature. The analysis of the annual time series of likely to be increasingly influenced by the Indian Ocean sea the temperature indices indicates that changes in temperature surface temperature [16]. In terms of all other rainfall indices, extremes over the 1966–2011 period reflect warming for the a mainly nonsignificant decreasing trend is observed that Djibouti City area. The trends in annual average minimum, may suggest a consistent change towards drier conditions as maximum,andmeantemperatures(ATN,ATX,andATM) emphasizedinthenorthernpartoftheGreatHornofAfrica presented in Figure 4 and given in Table 3 show a very [13] and in the eastern part of the Arab region [12]. significant increase of the three indices. Mean temperature ∘ ∘ All trends of temperature indices indicate serious signif- increased by 1.24 C(0.28 C per decade) during the 1966–2011 icant warming in Djibouti City. Mean temperature increased ∘ period. The warmest year of the entire series was 2010 with by 1.24 C during the 1966–2011 period and the period 2001– ∘ ∘ ∘ mean temperature of 31.3 C, which is 1.18 Cabovethe1971– 2011 was 0.66 C warmer than the 1971–2000 mean. This 2000 mean. The ten warmest years of the whole record have ∘ increase in temperature is much higher than the global been registered since 1998. The period 2001–2011 was 0.66 C warming [2] and is fully consistent with other studies carried warmer than the 1971–2000 mean (Table 3). out in the Arab region [12], over the Great Horn of Africa The annual number of warm and extremely warm days region [13], in the Arabian Peninsula [14], or in and nights, analyzed through the TX95p, TX99p, TN95p, and [17]. Extremely warm days characterized by daily maximum ∘ TN99p indices, has significantly increased. Extremely warm temperatures ≥45 C have become 15 times more frequent days and nights were 11.5 and 13.3 on average during 2001– than in the past (comparing the decades 1966–75 and 2002– ∘ 2011, a much higher figure than the averages of 4.7 and 3.8 2011 periods) while extremely cool nights (<18.7 C) have recorded during the 1971–2000 reference period (Table 3). almost disappeared. These impressive changes are observed Conversely, the number of cool and extremely cool nights at the global level [1] and are very significant in our region of and days, analyzed through TN5p, TN1p, TX5p, and TX1p, interest [12, 13]. 6 Journal of Climatology

35 36 30 34 25 C)

∘ 32 20

30 Days 15 10 28 5 Temperature ( Temperature 26 0 24 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011 year

ATN ATM TN1p ATX TN99p (a) (b) 25

20

15

Days 10

5

0 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011 year

TX1p TX99p (c)

Figure 4: Evolution of (a) ATN, ATX, and ATM; (b) extremely cool (TN1p) and warm (TN99p) nights; and (c) extremely cool (TX1p) and warm (TX99p) days in Djibouti City (1966–2011).

Table 3: Temperature trends analysis from 1966 to 2011 and averages calculated for the 1971–2000 and 2001–2011 periods.

ID Unit Average Trend (1966–2011) Significance Average 1971–2000 units/decade (P level) 2001–2011 ∘ ATN C 26.0 +0.27 <0.001 26.8 ∘ ATX C 34.2 +0.28 <0.001 34.8 ∘ ATM C 30.1 +0.28 <0.001 30.8 TN1p days 3.7 −1.2 0.014 1.4 TN5p days 19.1 −4.8 <0.001 9.2 TN95p days 18.8 +6.3 <0.001 38.3 TN99p days 3.8 +2.8 <0.001 13.3 TX1p days 4.0 −1.2 0.005 2.1 TX5p days 21.9 −9.0 <0.001 6.6 TX95p days 19.0 +3.8 <0.001 28.5 TX99p days 4.7 +2.7 <0.001 11.5

5. Impact of Extreme Weather in Recent Years exceptionally widespread drought in Ethiopia, the second driest year ever recorded after the historic year 1984 [15]. Since 2007, mean yearly rainfall (44 mm) has met a 73% In 2012, this period of consecutive dry year continued [18]. deficit when compared to the 30-year average (164 mm), a This impacted the well-being and, in some cases, the survival situation that is much worse than what was observed in the of the inhabitants of the Republic of Djibouti, especially early1980s.Yet,ithasbeenshownthat2009wasayearof rural population whose migration towards Djibouti City has Journal of Climatology 7 increased in recent years. By the end of 2011, nearly 19 million recorded at the station of Djibouti City over the last decades people were declared food insecure in , among justifies national and international concerns about the recent which 206,000 people are in the Republic of Djibouti: 120,000 drought and heatwaves. rural, 26,000 Somalian and Ethiopian refugees, and 60,000 Yet, with yearly precipitation ranging between 29 and urban [19, 20]. 66 mm between 2007 and 2011, the last 5-year period (average Drought is one of the main factors of migration to rainfall of 44 mm) has been the driest ever recorded since Djibouti City [21]. These new informal settlements continue 1980 with precipitation amount as low as 27% of the long- to grow in the south and west of the city avoiding the term mean (1981–2010). Such large rainfall shortages were restrictions put by the state and may be at risk [21]. Limited recorded elsewhere in the neighbouring of the access to risk knowledge may lead to settlements in risk- GreatHornofAfrica[15, 20] and partly explain recent food prone areas. Yet, the maximum daily rainfall recorded over insecurity in the country and the large migration fluxes those last five years was 46 mm in 2008. But we showed towards Djibouti City [19–21]. The conjunction of a very dry here that extreme daily rainfall events are characterized by period with the absence of extreme daily rainfall events and an amount over 108 mm. In addition, it has been reported limited access to risk knowledge increases the settlements that the maximum rainfall recorded during 1 day reached in -prone areas and contribute to flood vulnerability. 211 mm in Djibouti City [22]. Such rainfall occurred in the Local authorities have now to challenge two rainfall related past, and they will occur in the future. In addition, the hazards:thecurrentdroughtimpactandtheeffectsoffuture fourth IPCC report states that precipitation extremes are exceptional rainfalls with probable large damages in recent settlements. projected to increase worldwide independently of the trend ∘ in annual total precipitation [1]. Uncontrolled urbanization With an average mean temperature of 31.0 C, the 2007– 2011 period has been the hottest 5-year period ever recorded process may turn into catastrophic hazard in case of heavy ∘ rainfall as it has been seen elsewhere in arid zones of Africa since 1966, 0.9 Cwarmerthanthelong-termmean(1971– [23–26]. The latest dramatic flood that impacted Djibouti 2000). Extremely warm nights and days have become much occurred in 2004. It has been estimated that approximately more frequent than in the past while extremely cool nights 300 people died; 600 houses were destroyed and other 100 and days tend to disappear. These trends observed in the ones were inundated; 3,000 persons were made homeless; bordering countries [12–14] clearly have an impact on human and the lives of a total of 100,000 persons were affected27 [ ]. health that needs to be managed by national authorities. But the country also experienced killing floods in 1981, 1989, and 1994, systematically affecting over 100,000 people [28]. Acknowledgments The risk of flooding is therefore real. Moreover, since the rainfall decline in the Greater Horn of Africa is influenced This paper would not be possible without the collaboration of by the warming of the southern tropical Indian Ocean sea Mr. Osman Saad and Mr. Abdourahman Youssouf from the surface temperature [16], it is likely that migration from rural “Agence Nationale de la Met´ eorologie´ (ANM) de Djibouti” tourbanareasduetorainfallshortageswillnotstopnor who provided meteorological data. reverse in the coming decades. 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